{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Continuous Distribution Functions- Normal distribution\n",
    "\n",
    "- Exponential distribution\n",
    "- T-distribution\n",
    "- F-distribution\n",
    "- Logistic distribution\n",
    "- Lognormal distribution\n",
    "- Uniform distribution\n",
    "\n",
    "Author:  Thomas Haslwanter, Feb-2017"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "# Note: here I use the iPython approach, which is best suited for interactive work\n",
    "%pylab inline\n",
    "from scipy import stats\n",
    "matplotlib.rcParams.update({'font.size': 18})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Function Definition\n",
    "\n",
    "The following function will be used to show the different distributions functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "x = linspace(-10,10,201)\n",
    "def showDistribution(d1, d2, tTxt, xTxt, yTxt, legendTxt, xmin=-10, xmax=10):\n",
    "    '''Utility function to show the distributions, and add labels and title.'''\n",
    "    plot(x, d1.pdf(x))\n",
    "    if d2 != '':\n",
    "        plot(x, d2.pdf(x), 'r')\n",
    "        legend(legendTxt)\n",
    "    xlim(xmin, xmax)\n",
    "    title(tTxt)\n",
    "    xlabel(xTxt)\n",
    "    ylabel(yTxt)\n",
    "    show()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Normal distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
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NZk7REAtEJiy5ublUV1f3+Ljq6mpyc3OjUKKOWSAyxkeqypvrKpg/IZ+kMEfYXjAxn5Xb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\nKP5JS3O138WL3UR+xx8Pv/2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ItIpIlx1mIjJVRJ4UkSoRqROR10TkuFiVNxGJSImIaCdL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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2d32b03c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "showDistribution(stats.norm, stats.norm(loc=2, scale=4),\n",
    "                 'Normal Distribution', 'Z', 'P(Z)','')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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UllxqRM+Z2S/NbEauFzWzA8zsBuDZnhdNpP9KJDznMURJZsbUUY2qEUnJyWWF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\nkYiIxEqBSEREYvX/Ac7mZSUPxftiAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2d33cc7b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Exponential distribution\n",
    "showDistribution(stats.expon, stats.expon(loc=-2, scale=4),\n",
    "                 'Exponential Distribution', 'X', 'P(X)','')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Students' T-distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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hReTr5UliuD8bw+OIrG5g69Y8nAft3Vaqb9BEpJSb5VXnkVbRQnHEMCICfQkZ\n4p4dO1MjAlgVYG3FlbCtntK6UrfcR6mepolIKTdqdjRTWVZAeE0DuSFxpLmhW65VWlQgS7yt1a3S\nq3TNOdV/aCJSyo2KdhSRUuEAYKVfpFu65VqlRQaQ71r8NLNKnyXqrKysLO6///49+wX1lD/+8Y+c\ne+65pKamIiIkJycfsPzSpUuZOXMmQUFBBAcHc9JJJ5GVldWjMfVVmoiUcqO8qjwyXTPm1gREu7VF\nlOpa/LQhNp6R1R66L1EnZWVl8cADD/R4IpozZw6LFi0iLS2NsLADb4+2ZMkSjj32WAoKCnjwwQd5\n4IEHyMvLY/r06axZs6ZH4+qL7H6OSKkBrfUZIiNCUVicWx5mbdVad1VcMmPKK3lLW0S22rhxI6mp\nqQCMGTOGnTt37rfsLbfcgo+PD19//TXx8fEAnHfeeYwcOZLbb7+dzz//vFditou2iJRyo7zqPEbV\neLErJp5GLx+3TN1uFR7gQ5i/N8URw0ipaGFDZa7b7jVQ3H///VxxxRUAzJgxAxFBRLj88ssPue7W\nJHQw+fn5LFu2jHPPPXdPEgKIj4/n3HPP5YsvvmDbtm2HHE9fpi0ipdwovzqf62q8KY9Nci122pkt\ntrovLTKQ9cExTKlvYeeWTTicDjw9PN16z/7srLPOYuvWrcydO5c5c+YwcuRIANLS0nA6nVRXV3e6\nrvDwcDw8uv63/bJlywCYMmXKPueOOuooXnrpJVasWMEpp5zS5br7C01ESrlRXtUGkiua+SFjGMkR\n1kOn7pQaGcBPfpFcAaRUtFBcW0xyaHLP3WD2bOhrA+gTJsDTT3fr0nHjxjFlyhTmzp3LiSeeyHHH\nHbfnXGFhISkpKZ2uq6Cg4KATEjpSWmpNs2/bGmrVeqykpKTL9fYnmoiUcpNmRzP1xQX41ztZFxjt\n1vGhVmmRgbwxxFqFO6PKapH1aCIaRGJiYliwYEGXynfH7t3W/p++vvtuzebn57dXmYFKE5FSblK0\no4i0Smt1gxV+UYxx4/hQq7TIQEqCI3F6eZNR1Ux+dT4zU2f23A262fLoj/z8/Jg5swe/d/vh7291\n1zY2Nu5zrqGhYa8yA5UmIqXcpO1ip/mhcZzRCy2i1MgAnB6e1CUkMaJ6E99U57v9ngOVw+GgoqKi\n0+UjIyPx9Oz6eFxcXBzQcfdb67GOuu0GEk1ESrlJXnUemZXQ4utLaXCEWx9mbZUQ7o+Xh1AWk8To\ngmJe1kRdoWWXAAAgAElEQVR0UCIdj9sVFxf3yhjR5MmTAfjhhx+46qqr9jq3ZMkSRISJEyd2ud7+\nRBORUm6SX53PSTWe7IhPxoiHW6dut/L29CBxqD8FYXEcv6yZTZX6UOvBBAZafyC0nyHXW2NEw4cP\nZ9KkSbz77rv8/ve/39NCKi0t5d133+X444/vdt39hSYipdwkrzqPX9d4UZKcQGSQL8F+7lnstL3U\niEDWBUTz8xYnTQX5OI0TD9FHBvdn8uTJeHh48NBDD1FTU0NAQAApKSkceeSRhzRG9Prrr1NUVARA\nRUUFTU1N/OEPfwAgKSmJSy65ZE/ZP//5z8yYMYPp06dz8803A/DMM8/gdDp54okDbtc2IGgiUspN\nCso3kFDZxAfjY926tE97aVEBLPeNBCCpvInSulKGBQ/rtfv3N4mJibz00kv86U9/4vrrr6e5uZnL\nLruMI4888pDq/cc//sHixYv3OnbvvfcCcOyxx+6ViI4++mi++uor7rnnHu655x5EhKOPPpp3332X\n8ePHH1Ic/YEmIqXcoNnRDIWFeDkMWQHRvTI+1CotIpD5IVb3TusUbk1EB3bZZZdx2WWX9WidX331\nVZfKT5kyhYULF/ZoDP2FtteVcoPC7YV7pm6vC+idZ4hapUYGUBEQSnNAABm6HYTqBzQRKeUG+dX5\nZFZan28MH9YrExVapUYGggjbh6WQWSXk68w51cdpIlLKDfKqrWeIGkJC2TEkiLSI3msRtS5+WhKZ\nwKgaL/JrNBGpvk0TkVJukFeVx6hqTypjk/Hx8iA+bEiv3j81MpC8kFjiaprZXKbbQai+TRORUm6Q\nX5PPiBoPiiKGkTI0wO2LnbaXGhFA1pBoPAyY/HyMMb16f6W6QhORUm5QUppL1PZmsoNiSIvqvfGh\nVqmRgaz2jwIgoayBbTsH9n42qn/TRKRUD2t2NOO70XqQcaVfFKm9OD7UKjUygMLwvadwd5W2ogav\n3v6310SkVA9rO3U7PyzOlhZRWmQgdb4B7A4f2q1E5OnpSXNzs5uiU31dc3NztxZw7S5NREr1sNYZ\nc0aEotBYW1pEieHWJnxVcclkdiMRBQUFUVtb66boVF9XW1tLUFBQr91PE5FSPSy/Op/MKqiNiqHR\n27dXnyFq5ePlQWK4P5uHDmNEjWeXp3CHh4dTU1NDZWUlTU1N2k03CBhjaGpqorKykpqaGsLDw3vt\n3l1e4kdEMoDjgNFAFGCACmAtsNgYo3NF1aCWV5XHtGoPtsUkExXkS1AvLXbaXmpEADlBMUytc7Bt\ny/ouXevr60tiYiLV1dUUFhbicDjcFKXqSzw9PQkKCiIxMbHDHWPdpVOJSET8gCuAa4GxwP7mohoR\nWQM8D7xijGnokSiV6kfyqjaQUQWLh8f16tI+7aVGBrDCL4qrAI+8jRhj9rv3Tkd8fX2JjY0lNjbW\nfUEqRSe65kTkEmAD8CywHZiD1SJKAPyBANfnM4DfATuA54ANInKxW6JWqg/bXpRLYIOT1f7RtnTL\ntUqLDGSDa/HTuG27qNxdaVssSh1IZ1pEz7s+/mKMKdpPmRLXx2LgERFJAmYDfwfe6IlAleoPmh3N\nDNlUDEB2UAwzbG0RBVIcGoPTw4OMKif51flEBkTaFo9S+9OZyQqpxpjbD5CE9mGMKTLG/BpI635o\nSvU/BdsLGO6aul0QHm9riyg1MoAmL292RMdaq3BX6yrcqm86aCIyxpR1t3JjjD7OrQaV/Op8Mqqg\nxdubkuBIW8eIhgb4EDLEm/LopG4/1KpUb+jU9G0RiepKpSJyavfCUap/y6uyniGqjE3Ez8eb+NDe\nXey0LRFheFQgG8PiyawW8nVfItVHdfY5onUicu7BColIiIi8BnxwaGEp1T/lV+czstqD4ogEhkcF\n4tHLi522lxEdyKohUQQ2GrYX5Ngai1L709lEVA38U0T+KSIdPuXkagVlAxcDL3SmUhHxEJFfi8h6\nEWkQkWIReUJEDtqxLiIZIvKgiCwRkQoRqRORLBH5XWeuV8odNlbkklrlZF1QLOlR9nXLtRoeFcS6\nwBgAPPM22hyNUh3rbCIajzV9+1xgrYic0XrC1Qp6FasV1Az8zBhzXSfrfQp4EiuB3Qy8C9wC/EdE\nDhbbr4BfAxuBB4E7gFzgD8D3ImJfn4gatBrzcvBywtqAaNKje2+JlP3JiA6kIDwegNitO6mur7Y5\nIqX21alEZIxpMMbcCpwANALzReQ1ETkfK4lcgtUKGmOM+aIzdYrIaKzkM98Yc5Yx5gVjzG3AbVjP\nJF1wkCr+BQwzxlxkjHnGGPO8MeZ84CFgHHBlZ+JQqqc0OZoI2lQCQP7QhD7RIkqPCqI0OIJmb2+d\nsKD6rC6tNWeM+QprZYV5wEXAW7RpBRljdnahuguxVmh4ut3xF4DdWF18B4pluTFmRwen3na9julC\nLEodssLthWRWWGuybRw6jPRo+xNRdLAvgX4+lMcM00Sk+qzuLHo6BTgGK4kYrJUVhnajnsmAE/ix\n7UHXskBZrvPdMcz12u1p50p1R15VHiMqYXtoOM2BQQwL87c7JESE9OhAiocmaiJSfVanE5GIBIjI\n88CnWEloFjAVqALeEpF3RCSiC/eOAyqNMY0dnCsBIkTEpwv1ISKewL1AC1Zr7UBlrxGR5SKyvKKi\noiu3UapD+dX5jKyALTHJpEUG9vr24PuTHhVETlAMaTWwqULXJFZ9T2efI5oBrAGuwVqyZ4wx5lNj\nzFKsiQx/Bs7CmuZ9difv7Y813tSRhjZluuJprBbbfcaY3AMVNMbMNcZMMsZMiozUZU/Uocur2sCI\nKsgNGUZGH5io0Co9OpDswBi8nbBrwzq7w1FqH51tEX0B+AFnGGMuazs2Y4xpdE0ymAHUAe+IyLxO\n1Lkb2N86435tynSKiPweuAmYa4z5Y2evU6qnVBasI7QBVgXFMrwPTFRolR4dxCbXzDmv/E02R6PU\nvjqbiP4JjDbG/Gd/BYwx32DNVnsea5r3wZRidb91lIzisbrtmjoTnIjcD9wDvAx0duq4Uj1K1lt7\n/mwcmtCnWkRtp3BHl9ZSU19jc0RK7a2z07cvMsYc9H+vMWa3MeZG4GedqHaZ6/5HtD3o2vtoArC8\nM7G5ktD/Aa8CVxndSlLZoL65nrBCa37MxvBhfWLqdquYYD+aQsPZ5R9ARhXkVh2w11qpXueWrcKN\nMYs6UextrFl3s9sdvxprbOjN1gMikiYiI9pXICL3YSWh14FfGWOc3Q5aqUOQX53PiAqo9/OjJiyS\nhHD7Z8y1EhGGRwdREplgJaJKTUSqbznofkQiktHd7b9FJHN/kwaMMWtE5DngJhGZD3wMjMRaWWEx\ne896Wwgk0WZnWBG5EXgA2Iw1hvXLdrtPlhljFnQnbqW6KrcqlxGVUBKVSFpUUJ+ZMdcqIzqQ/NB4\nxhasZ5G2iFQf05mN8daJyOvAk8aYtZ2pVEQOw1oh4QLA+wBFZwOFWLPxTgEqgWewZr0drHXT+pxR\nIla3XHuLAU1EqlfkVuZyaSWsTUvsEw+ytpceFcS64Dhm1ULRlk79GCvVazqTiE4HHgdWichq4COs\n8Z2NWIuhChAOpANHYT1fNBJr6Z8DbgdhjHEAT7g+DlQuuYNjlwOXdyJ+pdyuaMtaEmphXlBcn5qo\n0Co9OpC3IhIBcK7VRKT6loMmImPMJyLyOXAecAMwB2tsp73WvoivsLrM3tMxGzVYNGavBqylfc7q\nQxMVWqVHB7HBlYiC84txOB14enjaHJVSls60iFpbLvOAeSISDRwLjAIisZJSBbAWWGyMqXRTrEr1\nScYYfPMKAMgP7xuLnbYXF+JHVVQ8Td7eZJQ1U7SjiNSwVLvDUgroZCJqJSKRQDKwwhjzjlsiUqqf\nKd9VTtLWehweHmyLjCOxD82YayUipMaGUhyVwOjyTeRW5moiUn1GZ5f48XCtM7cV+B7YICLfuhKT\nUoNa64y50sg4EqJD8fJ0y1MRhyw9KpDcocmMqtBniVTf0tmfmJuwZrZtA+ZjrTt3NPB3N8WlVL+R\nW5nLyArYGJ7AiJi+N1Gh1YiYINaGDiOxFoo2r7E7HKX26GwiuhTIAUYaY841xkwA/gGcJiKhbotO\nqX4gryyb4TWQHRLPyNhgu8PZr5GxwWyISAKgaU2WzdEo9T+dTUSZwCvGmLo2x54BPIGMHo9KqX6k\ndv0qfBxWi6jvJyJr5tyQDbr4qeo7OpuIArAWKW2rtM05pQYtj/XWeEv+0GF9OhGFB/jQlJBIg7cP\ncZu3s7OpKxsqK+U+XRlVbf/sUOvXfWstE6V6UbOjmbCCbQBsT0wlMmh/O5v0DZlxoRRGJTC6AjZU\n6SZ5qm/oyvTtWSIS0+Zrf6xkdK6ITGhX1hhjnjrk6JTq4zbVbGJUmZOtoZEkpsTaHc5BjYwNJics\nkclFG/mmMpfDYw+3OySlupSIfun6aO/aDo4ZQBORGvByq3IZWwbrI5L7dLdcq5GxQeQMTeIXa6Go\naBWMvdDukJTqdCKa4dYolOqn8rZlc1Il/CMliZGxfXfqdqtRscF84JqwsHvVioOsBqlU7+jsEj+L\n3R2IUv3RjjXL8HFCbmQSM/pBiyglIoCiaGsKt3eOPtSq+oa++Qi4Uv2ErFsHwKaYFNIi+94ac+15\neXoQmDmcem8fwgu2ohsaq75AE5FShyBkQzEtHh54jxqJdx9d2qe90QlhbIxIJGNbCyV1JXaHo5Qm\nIqW6q6a+htSS3RSGxzEiuf8suzg2PoTcoYmMLvfQbcNVn6CJSKluyq7IZmy5J+uHJjM2PsTucDpt\nbHwIGyISidvpZOPG5XaHo5QmIqW6K3fzT6TVOMiNTGJMP0pEGdFBbIqyJizs+Ol7m6NRShORUt22\nfdk3AGyMTumT24Pvj4+XB82jxwDgsXadzdEopYlIqW7zXG1tpdAwdjw+Xv3rRyl2dDo1QwKJyC3W\nmXPKdv3rp0epPiRs/Wa2+wUSPab/LUA/Zlgo66LSGFXipGxXmd3hqEFOE5FS3VBTX8OIzc1kR6Uy\ndlj/25JrXHwo2VGpjCl3kl262u5w1CCniUipbli3dRVjyx1kR6VwWGL/S0SZMUHkxaYypMVJ6Yov\n7Q5HDXKaiJTqhtKfFjOkxUle3PB+NVGhlY+XBy3jrEXzm1b8aHM0arDTRKRUN9Qv+wEAM348nh79\nc0uuqEljafT0xm+t7kuk7KWJSKlu8FmTS6OnF5GTx9sdSreNT40iNzKJuPwdOnNO2UoTkVJdZIwh\nNq+GvIgkxqdG2R1Otx2WaE1YGFvaQEntFrvDUYOYJiKluqhs5zbGlexmTXQaE/rhRIVWsSFD2JQ4\nnKH1zeT99IXd4ahBTBORUl204cdPCa9vZmNyBlFBfnaHc0haJk4CYPs3C2yORA1mmoiU6qI9v7Qn\nT7I3kB4QP30KjZ5e8OMau0NRg5gmIqW66sd1NHp6k3LcVLsjOWSTMmLIiUohNqfc7lDUIKaJSKku\nil2/jeyoVI5Ij7Y7lEM2Oi6YtbHDGb2lhvrGXXaHowYpTURKdUFj425GbalhbXwaw6P6/tbgB+Pl\n6cHWzHSCmprZtOQTu8NRg5QmIqW6oGDJJwQ0N1M+Mh2R/vkga3v+U48EoPTLz2yORA1WmoiU6oIt\nC6xf1oHTjrQ5kp5z2Mzj2eXth+N7nbCg7GFrIhIRDxH5tYisF5EGESkWkSdEJKCT1/9WRN4VkU0i\nYkSk0M0hq0HO+V0Wtb4BHPnzmXaH0mMOT41kdexwhuVstjsUNUjZ3SJ6CngSyAZuBt4FbgH+IyKd\nie1h4HhgI1DjriCVapWSXcRP8emMGTbU7lB6jJ+3J+tSUxlRUoajrtbucNQgZFsiEpHRWMlnvjHm\nLGPMC8aY24DbgBnABZ2oJs0YM9QYcyJQ6sZwlaKlqpL08nJy05Px8rT7b7ieVTdpFF7GSe5H79kd\nihqE7PxpuhAQ4Ol2x18AdgMXH6wCY8wmN8SlVIfWzH8HgIYjx9gcSc9LOe1EADZ/pBMWVO+zMxFN\nBpzAXpuhGGMagCzXeaX6jLLPFtIiHow542S7Q+lxJ02ZxoahwwhZsc7uUNQgZGciigMqjTGNHZwr\nASJExMddNxeRa0RkuYgsr6iocNdt1AASkZVNdlQCx44/wu5Qepyftw9ZyfGMKtiEcTjsDkcNMnYm\nIn+goyQE0NCmjFsYY+YaYyYZYyZFRka66zZqgGhpbGLU5gJWp8bi5elldzhuUTo2kZCG3Wz+foXd\noahBxs5EtBvw3c85vzZllLLd+o+/wr+5kbLDkuwOxW2Cf2b1hue88y+bI1GDjZ2JqBSr+62jZBSP\n1W3X1MsxKdWhon9Zs8kiT59ucyTuc+TxJ1MaFIbfN9/ZHYoaZOxMRMtc99+rw11E/IAJwHI7glKq\nI+E//khOZDRTJv3M7lDcZmTUKL5NiWTshrXU7t5fr7lSPc/ORPQ2YIDZ7Y5fjTU29GbrARFJE5ER\nvRibUnsUba1hfFEO36WGMDx8uN3huI2HeJA3IZKh9bWs/ORbu8NRg4hto67GmDUi8hxwk4jMBz4G\nRmKtrLAYeKtN8YVAEtZzR3uIyCWu4wCRgI+I3OP6usgY87ob34IaJNa8v4BTmxvZckT0gFnodH/8\nTpoEr31HxQcfw9kn2B2OGiTsnv4zGygErgFOASqBZ4D7jDHOTlx/JXBsu2O/d70uBjQRqUO285PP\ncCIEn9T+v9rAM2byyWwKe4Xwpd/R4nAOuBUkVN9kayIyxjiAJ1wfByqXvJ/jx/V8VEr9T0VdI8mr\nfmR1TBiHjxr4LYQjhx3J+8m+nJ29lu9zyzhmVKzdIalBQP/cUeoAvliSy8SSHD4f7mBy3MBf7CPU\nL5TVhw8huHEXa9/T5X5U79BEpNQBlP7rv3g7Haw/KooAn07tTtLvOU44lhYRfD7/lKaWzvSQK3Vo\nNBEptR9ltQ0MW/IV2/18CDn253aH02smjTqBHxICmbJhGd/m6/JXyv00ESm1H/9dVcqMjcv5PNWT\nY4cP/PGhVjOSZ/Df9F2MLt/E4kVZdoejBgFNREp1wBjDTx8sImpXDR9n1HNs0sCfMdcqISSBNZPi\nAGj5+BNqG5ptjkgNdJqIlOrA2pJa0pZ+hVNgy9FjCBsSZndIvSp+ys/ZEuLNsRuW8t9VW+0ORw1w\nmoiU6sA7y4uZteF7fkjwYvy4gbusz/7MSD2e9zKbObZgBR9+m2t3OGqA00SkVDsNzQ6yFi5lRHkB\n74xqYUbKDLtD6nXHJR/Hv0aDb0szkYsXsKGszu6Q1ACmiUipdj7IKmH66q+tz0d5MD1x4K64vT9x\nQXFUTcigKsSXU/K+5/UfiuwOSQ1gmoiUasMYw8vfFfKLTUtYleJP4piphPiF2B2WLX6eMYt3M5s5\nftNyPl6Sz456nbSg3EMTkVJt/LCpivqcXNK3bOC19N2ckn6K3SHZZlb6LP450olPUyNTcn7gnWXF\ndoekBihNREq18dK3hVyy/kucHsK8MdYv48HqmKRj+Gm4PzURAVy58Rte+b6QFoeutKB6niYipVxy\nttayaF0p5+d8ycpxUXgNS2BM1Bi7w7KNr5cvxw8/kTcO82RCzlJaiov5d1ap3WGpAUgTkVIuzy7K\nZ2bpOoIqtvHnEduZlT5rwO8/dDCz0mfxlxG1iNPJtZt/4Lkv87VVpHqcJiKlgA1ldXy8diu/LvmO\nppBA3klr5NSMU+0Oy3anpJ9C/lDYPDaJ89Z+QUHFTv6zWltFqmdpIlIKeOyzXBIaaxnx/QIWTxuG\nX2AIJ6aeaHdYtosPjmdqwlTmTnAQWLiR83fm89SCPBpbHHaHpgYQTURq0PthYxULsst4vHoJ0tTE\n3Zlb+MXIX+Dr5Wt3aH3C+aPP5/HELbREhHNHzqdsrt6tzxWpHqWJSA1qTqfhDx9lkxzoyeRP36bs\n2En8FLyT80adZ3dofcbZo86myVv4/uQxRHz1OeeENvLnhXlU72qyOzQ1QGgiUoPaG0uLWFday5Mm\nFykr45XpQYT5hTEzdabdofUZcUFxHJN0DPdmlmI8Pfld/ufsbnLwyCc5doemBghNRGrQ2rqjnkc/\nzeXY1FAOe+OvOMaM4ve+Szh31Ll4e3rbHV6fcuGYC/m6JZ+qX/ycsDdf5dbRgbyzfAvfb6y0OzQ1\nAGgiUoOSMYZ7/72WFqeTJxw5yIYNLLhkKrsc9Vw98Wq7w+tzLhx7If7e/jx5gj80N3PD0vdIGurP\nnPlr2N3UYnd4qp/TRKQGpTeWFPFFTjl3nTCciKcexYwbx28DlzIhZgITYyfaHV6fE+wbzAWjL+Av\nVR/T9MsL8HphLk9Mi6KoejcPfJhtd3iqn9NEpAadnK21/P6jHGZkRnL52s8gL4/8Wy4mq2I11xx+\nzaB/iHV/rpl4Dbuad/HeWSOgpYVJLz7JjccN5+3lxXy4Sp8tUt2niUgNKtW7mrj6teWEDvHm8eOH\nIffdBzNm8GDYKgK8A/jl2F/aHWKfdUT8EYyPHs8fSudhbrkFXn6Z2SHbmZgUxl3/Ws260h12h6j6\nKU1EatBobHFw/RsrKK9r5O+XTGToI7+H2lq2/P4O5q39J9dMvGbQbvnQGSLCHUffQXZFNh9fOAmi\novCafSt/u3ACof7eXP3qcsrrGuwOU/VDmojUoNDicDL7n1ksLajmsXPGcdjGLHj+ebjpJv64/b94\niAe3TbnN7jD7vPPHnE9KaAq/z/oz5tFHYelSol56nhcunUTN7mYu/cePbN+tzxeprtFEpAa8FoeT\nO/+1mk/WbuPeU0dxRmoQXHEFpKez9bc381LWS1w6/lKGBQ+zO9Q+z8vDizuOvoOlJUtZODUWTjsN\n5sxhzI4S5l46kU0Vu7js5WW6iZ7qEk1EakBraHZw41s/MX9lCb/5WQZXTk2Ga66B4mJ47TV+t+Qh\nHE4Hv532W7tD7TeuOOwKEkMSueOLO3H8/XkICoILLmB6nD/P/vIwskt3cMHcJVTUNdodquonNBGp\nAauirpGLX1zKZ+vKuO/UUdx0fDo89hi8/TY8/DArEr15JesVZh81m7TwNLvD7Tf8vPx4dOajZG3L\n4pWtn8Abb8C6dfCrX/GzUdH847LJFFbu4sznviNna63d4ap+QBORGpCWF1Zz+rPfsrZ0B89ceBi/\nmpYC770Hv/0tnH8+jt/czs2f3ExkQCT3HHOP3eH2O+eNPo+jE45mzqI5VE2fBA8/DO+8A/feyzEZ\nkfzzmqNocTo566/f8++VJXaHq/o4TURqQGlodvDk57mc9/cf8PIU/nXd0Zw2Pg4+/RQuvBCOOgr+\n8Q8e/+EJftjyA4+f+DjBvsF2h93viAjPzXqOmvoabvj4Bswdd8CVV8JDD8FjjzE+IZT/3DSNMfHB\nzH47i9n/XEnVTu2qUx3zsjsApXqCMYYvcsp58L/rKK6u56zD43ng9NEE+Xlbf6lfcgmMGQMffURW\nXR73fnkvZ488m4vHXWx36P3WhJgJ3H/c/fxu0e84LeM0Lv7736GuDu68E3buJOr++5l39VE89+VG\nnlmUx6L15fzm55n88ohEvDz1b2D1P2KMsTsG202aNMksX77c7jBUN60q3s5TX2zgq9wK0qMCeeCM\n0RydFgFOJzz6KMyZA1Onwocfss27kSNfPJIWZwurrltFhH+E3eH3ay3OFma8OoMVpStYfPliJkdN\ngGuvhZdfhksvhb/9Dfz9yS+v4/4Ps/k2v5IRMUHc8fNMZmRG4eGhq1j0ZyKywhgz6ZDr0USkiag/\nMsbw1YYK/r54I0s2VRPk58XsmRlcOiUJb08P2LYNrroKPvoIzjsPXnmFOo8WTnjtBNZVrOPry79m\nYpyuKdcTyneVc+SLR1LfXM/3V35PamgKPPggPPCA1Qp96y0YMwZjDJ+u3cZDH+ewpaae9KhArjkm\nlTMmxOPjpS2k/kgTUQ/SRNR/FFTu4v2VJfx7ZQmbq3cTE+zHVdNTuOCIRAJ9vaClxfpr/M47Yfdu\nePJJuOEGquqrmfXWLFaUrmD++fM5PfN0u9/KgJJdkc20l6YxxHsICy5ZwKjIUfDZZ1aX6Pbt1r/H\n3XdDYCDNDicfrd7K84s3sn5bHeEBPpw2LpZfHD6M8cNCdK2/fkQTUQ/SRNR3OZyGrOLtLM4t58vc\nCtaU7EAEjk4bytmHD+PUcXHWX9MtLTB/vvVXeHY2HHMMzJ0LmZmsLlvNue+eS9H2It459x1NQm6y\ntnwtJ75+Ik2OJl4981VOzTgVKivhttvg9dchOhruust6mDg0FGMMX+dV8s6yYhbklNHU4iR5qD8z\nRkRxbEYkR6UOxc/b0+63pQ5gwCQiEfEAbgWuBZKBCuAd4D5jzC53Xw+aiPqSHbubWVu6g5+Kavhp\ncw0rimqobWjBQ+CwxDB+NiqaMybEExPiZ12QkwPz5sFrr0FREWRmWlOJf/ELmpzN/GXpX7hn0T2E\nDwnn7XPeZnrSdHvf4AC3qWYTZ79zNlnbsrhh0g384fg/EDYkDJYssVpEixeDvz9cdBFcdx0cdhiI\nUNvQzKdrtvHfNVtZuqmKxhYnvl4eTEgI5fCkMA5PDGP8sBAig3y1xdSHDKRE9GfgFuB94BNgJHAz\n8A0w0xjjdOf1oImotzU7nGzb0UDJ9noKK3exoWwneeV1bCiro6z2f1N806MCmZgUxrT0CKYPjyTE\n39vqbvvhB+sX2n/+A1lZ4OEBxx8PN90Ep51Go7OZN9e8ySPfPkJedR6nZZzGi6e/SFRAlI3vevBo\naGngrgV38eyyZwnzC+P2Kbdz7aRrCR8SDitXwl//Cm++CfX1kJgIs2bBKafAtGkQGkpDs4OlBdUs\nzq1gRVE160praXFav6dChniTER1IenQQGVGBpEUFEh86hLjQIdp6ssGASEQiMhpYA7xvjDm7zfGb\ngb8AFxlj3nLX9a00ER0aYwy7mxzsbGyhrqGZqp1NVO1yfexspHpXE1U7myirtZJPWW0Dzjb/7fy8\nPXhc2SUAAA09SURBVEiPCiI9OpCM6CBGxARxWHQAIVXboKAA1q61PtassX6RNTeDpycccQRccAGc\ndx61Yf58XfQ1H+Z+yHs571FdX8246HE8csIjnJx+sn3fnEEsa1sWd39xN59t/Aw/Lz9OzTiVMzLP\nYGrCVJJNCDJ/vjWZZMEC2OXqvMjIgMmTYfx46/P0dBoSklhT1ci6kh38f3t3G2NHdd9x/Pu7D7uX\n3a1xvcbexIlIwNgGTApBwcGpCAkkUYPaIqW8qJqqqE2oqoY8iFe0aquoTRqpykMh7Qu3qpq0VCWW\nQttUNEgJJXVJKZAQMIYSHmQebMfGNn5Y4324d/59ceau767vetfeuzt3d38faTQzZ87ce3w8O/+Z\nM3PP+emBYZ7ff5yf7h8+rT+71QM9rFt5HkPn1xgc6GWwv4dV/T0Ty4MDPayoVRmoVejvqVD2G3tz\ntlQC0Z8BfwhcFxE7WtJrwCHgBxHx0fnav2mhA1FEEAHRXIZ8PaUzZX1SvgwaEdSzjCyDepbRyOLU\nFEG9cWq5dVs9C7J8fiotY7SeT+MNRusZY831eiNPP7U8Mt7g+Eid4dE6J0brDI/UOTE6RqXeoJLV\nqWQNKlmDctagmtWpNBr8fBWGqg3eUmqwrqfBUDljTbnOauoMNkY4f/gNdOhQep5w8CDs2wd790LL\nsZkNDjJ62QaOXHEJr1x1Ec9tXM3z4z/j6defZteBXbz4xotkkdFf7efmTTdz65W3csM7b3AzThd4\nav9TbPvRNrY/s50DJw4AMDQwxJZ1W1i/aj0X9a3jqhdOsO6ZV1m58wX6n9xFed/+yR+yahUMDU1M\nsWYNJ2r9HFIPh0o1DlBlX1bltUaVffUSh0aDg2PBaKnCeLlCPZ+PlSuMl6s0VKKvt8JAc6qleV9P\nhd5qid5yKc0rZXorpTRVTy33VNK2arlEuSTKJVGZMj+VnvJUynmaNGldiJLSj4RLAiFUAgElCTXT\nBFKe1rqtwGN8qQSiB4Abgb6IGJ2y7WFgQ0RcMF/7N11R6Yn7Vl6AJupCpNN/vtZSRepQ+uw+P9qn\nt3zKdHlo85mT8878GSk98upopgciqGQZ5Syj2mjMuXuO4z1waKDEoT5xuF8cGCjx6krx0ooGz6+o\n88wFcGDg9P3KKnPJ4CVcfsHlbF6zmesuvI6tb99KrVKbY4lsPjSyBrte38XDrzzMD1/7IY/vfZzd\nR3YzUj99DKPzT8KGw3DpGxUuPiLeMiyGhmHt8WDNcMYFxzP6x8793JUJ6qVSOpolMolAZCoRSmnN\n9bTtVHrWuo9K6QJxhmAQzLD9DJtn3rd1+9nXyZm+u/33n/qODYf2LolAtBNYExFr22z7FnAL0BsR\nbQc4mcv+km4DbgNYX6td/dcbNwF5Fef1PiksTfxnR7osObWWsqv5HxYTy8pzTDpQWhZDmliddDBM\nytNahpbNzTyKieWJdMVEfjXz5NvUDCzNfQRSQCkFGDX3n/j8ln9rfmUG0CiVyMqiUSnTqOTL5RJZ\nuUxWLtGolGiURVYp0yiXGKtVGa1VGKv1MFarpqmvh5HzqtR7KnnxJh/wvZVe+qv99FX7JqbBvkHW\n9q9laGCIoYEheiu92OIVERw4cYCXj77M4ZOHOTZ6jKMjRzk6epRjo8cYa4xRz+oTUyNrpOWo0xgf\no3pyjPNOjlM7Oc55J+vUTo7TO1qn3Mio1PNpPJtYL9cbLWmBIv2tKEvLBJSmzBWBsnw5E4RQxsRc\nWToL5Jd7EK0nb+VNGkzJ0zw7aNKF4NRLztO2TTldN/+0pwtWky9+dVqY0kyn/zNsV8CHdj7ZkUBU\ndBc/fcB0HVCNtOSZbqStc94/IrYB2yA1zX3Iz4jMFpwk1g6sZe3AadeSthh0qFmw6J8zvwlMd0lb\na8kzX/ubmVnBig5Ee4HVktoFk3XAwema5Tq0v5mZFazoQPRYXoZrWhPzt96uBGZqL5vr/mZmVrCi\nA9G9pMdhn52S/knSs517mgmSLpa06Vz3NzOz7lToywoRsVPSXwGfkvRt4H5SzwifBn4AtP4Y9fvA\nhbS8U3aW+5uZWRcq+q05SHczu0mvUt8EHATuJvUVN2P3PB3Y38zMClR4X3PdwF38mJmdvU71rFD0\nMyIzM1vmfEcESDoOPFd0OZaI1aTmUesM12dnuT47a2NE/NxcP6QbnhF1g+c6cXtpIOlx12XnuD47\ny/XZWZI68kzDTXNmZlYoByIzMyuUA1GyregCLCGuy85yfXaW67OzOlKfflnBzMwK5TsiMzMrlAOR\nmZkVyoHIzMwKtawDkaTflXSPpP+T1JDOPHCupI2S/kXSG5JOSNoh6YMLVd7FSNJuSTHNtLro8nUj\nSSVJn8uPyxFJr0r6sqT+osu22Jzh2BsuumzdTNKdkrZLeimvr90z5N8i6XuSjks6Jum7kq6c9fct\n55cV8sodBJ4A3gm8LSLajn0r6WLgUaAOfA04ShpuYjPwSxHxvYUo82KT1/FJ4AttNm+PiOmGel+2\nJP0lqQf5+4D/IPUofzuwA7jRnfnOXn5xuYPT3+4aj4h7CyjSopDX22Hgx8DVwLGIeMc0ed8LPATs\nAb6eJ38KWANsjYidM37fMg9E7wBeiYhM0r8DN50hEH0L+BhwdUT8JE8bAHYBI8CmWM6VOY08EO2O\niOsLLsqiIOlyYCdwX0R8rCX9duAu4DciwsObzFJ+Qv1GRNxadFkWE0kXRcRL+fLTwMAZAtGjwCbg\n0ojYk6etA54FHomID8/0fcu6aS4ids/m6jJvEvkV4KFmEMr3Hwb+FtgAvGfeCroESKpIWlF0ORaB\nXyeNufW1Kel/A7wJfHzBS7QESOrJLxxtFppBaCaS1pPOfdubQSjffw+wHbhR0tBMn7OsA9FZeBfQ\nC/xPm22P5HMHoultIZ1Ej0o6Iukbkt5adKG61HuAjNQMPCEiRoCf4OPsXPwa6fg7LumApLslnV90\noZaI5vE43blRpKa9M3Knp7PTPGnuabOtmbZugcqy2Owi3TU+C1SB64FPADdIuiYi9hZYtm70VuDg\nNM/O9gBbJfVExNgCl2uxepR0Zf4CsAL4KOn5xfslbc1bNezcdeTcuOgDkaSVpFFaZ+uuiDh8ll/T\nl8/bnRxGpuRZcuZSxxFx05Rt/yzpv4B7gM+TXviwU/pof5zB5GPNgWgWImLLlKRvSnqK9PLMZ2j/\nEo3NXkfOjYs+EAErgT85i/z/SHob5Gy8mc9722yrTcmzFHW0jiPinyR9gTS0u032Julto3aWw7G2\nEP6CdDzfhAPRXHXk3LjoA1FE7Ca1Q86nZvNRu1vMZlq7W9MlYZ7qeDfwvg5/5lKwF7hMUm+b5rl1\npGY73w3NQUSMS9pLGiTP5qYj50a/rDA7O0m3nte22fbefN6RAaKWkfXA/qIL0YUeI/1dXtOaKKkG\nXImPsznL6/Jt+PjrhMfy+XTnxgB+NNOHOBDNQv5A8zvA9ZJ+oZmevw76CeB5przlZCBp1TTpv086\nEXxnYUu0KNxL+uOd+kzuk6S29nsWvESLlKTBaTb9Kak1yMffHEXEC6SLo1ta34TNl28BHoyIn830\nOcv9B62/DDQDy8eBjcAf5etHIuLrLXnXk4LNOPBV4Bjp5HAF6YewDyxUuRcLSZ8Ffgf4LqkprkJ6\na+5m4EXg2oh4vajydStJd5Pe7LoPuJ/Us8KngYeBD7pnhdmR9FXSVfl/Aq8AA6S35j4A/C/wgYg4\nWVwJu5ek3wQuzFdvB3qAL+frL0fEP7Tk3Uqq49eAu1v2WQu8LyKenPELI2LZTsDfk64+20272+S/\nFPhX4AjpAdx/k7pcKfzf0o0T6RnQv5FOAidJb9E8C3wJWFl0+bp1AsrAHcBzpCbhPcBXSL9uL7x8\ni2UCfhV4IK+/EeAE6bdYfwDUii5fN0+kLnumOzc+1Cb/tcD3gWHgeF7v757t9y3rOyIzMyuenxGZ\nmVmhHIjMzKxQDkRmZlYoByIzMyuUA5GZmRXKgcjMzArlQGRmZoVyIDIzs0I5EJl1CUlflBSSfrvN\nNkl6SNKopM1FlM9svrhnBbMuIamH1FPx24HNEfFay7bPkbr5uTMivlRQEc3mhQORWReR9G5Sh5wP\nRsRH8rSNwBPAU6ROJBsFFtGs49w0Z9ZFIuLHwJ8DH5Z0m6Qy8E3SwIS/5SBkS5HviMy6jKQqacCx\ni0jDrv8ecEdEfKXQgpnNEwcisy6UD8D4GFAlDTfy/vA4RLZEuWnOrDsdJY1FBHC/g5AtZb4jMusy\nkgQ8CGwljWR7IfCuiHix0IKZzRPfEZl1n9tJQ6p/HriFNMT63+UBymzJ8R2RWReRdAlpOOtdwLUR\n0ZB0J/BF4DMRcVehBTSbBw5EZl1CUgnYAVwNXBURz+bpZeAR4DLcRGdLkJvmzLrHHaTnQn/cDEIA\n+W+HbsVNdLZE+Y7IrAtIupTUe8ITwC+2++Gqm+hsqXIgMjOzQrlpzszMCuVAZGZmhXIgMjOzQjkQ\nmZlZoRyIzMysUA5EZmZWKAciMzMrlAORmZkVyoHIzMwK9f+ilijVKO+KMwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2d336c4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ... with 4, and with 10 degrees of freedom (DOF)\n",
    "plot(x, stats.norm.pdf(x), 'g')\n",
    "showDistribution(stats.t(4), stats.t(10),\n",
    "                 'T-Distribution', 'X', 'P(X)',['normal', 't=4', 't=10'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## F-distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Programs\\WinPython-64bit-3.6.0.1Qt5\\python-3.6.0.amd64\\lib\\site-packages\\scipy\\stats\\_continuous_distns.py:1415: RuntimeWarning: divide by zero encountered in log\n",
      "  lPx = m/2 * log(m) + n/2 * log(n) + (n/2 - 1) * log(x)\n"
     ]
    },
    {
     "data": {
      "image/png": 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C65XWgnwiJPp9VFQ3MXYpOO2QBSLjERKtd9SBYvjw4bpw4cKo56xYsYLBB1A1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\nIgBWAbVBwKzT1anYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2d36ed828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ... with (3,4) and (10,15) DOF\n",
    "showDistribution(stats.f(3,4), stats.f(10,15),\n",
    "                 'F-Distribution', 'F', 'P(F)',['(3,4) DOF', '(10,15) DOF'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Uniform distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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IdgVqwA2NhRGxCri52D8emxbbB8ffNLNqDZeZ9FTyrDnLWpWBaCawIiKeabFv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\nCYgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2d32a6f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "showDistribution(stats.uniform,'' ,\n",
    "                 'Uniform Distribution', 'X', 'P(X)','')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Logistic distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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m6tSppra2tt6xjz76qOnbt68JDQ01gLn33nuNMca8+uqrBjCff/55vfLl5eXm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\nz1fvoldCJAN7xPm5cu1XRKiDY/qn8Pm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uDTNJCyT9QNI/JL0oabukq6Yq3l4kaVhStHmc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\nzKyo/wBW/NJH1LttTgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2d47d6d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "showDistribution(stats.norm, stats.logistic,\n",
    "                 'Logistic Distribution', 'X', 'P(X)',['Normal', 'Logistic'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Lognormal distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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R6Rclos2ExNNQUwlAS4dqRSIipaZElEV9TRWg2RVERMpBiSgm3kcEmoFbRKQclIiy6EpE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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2d485ac18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = logspace(-9,1,1001)+1e-9\n",
    "showDistribution(stats.lognorm(2), '',\n",
    "                 'Lognormal Distribution', 'X', 'lognorm(X)','', xmin=-0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1f2d47ca518>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/ZDx3VZ1Qi7hMjJu5dg+b9x3h7jE9vA6l3kpvkszJPVvzxoIt/OKUbiQl2O1L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\nt69LItJNRP4oInNEZLf7eVssIvfW4Hi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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f2d48223c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The log-lin plot has to be done by hand:\n",
    "plot(log(x), stats.lognorm.pdf(x,2))\n",
    "xlim(-10, 4)\n",
    "title('Lognormal Distribution')\n",
    "xlabel('log(X)')\n",
    "ylabel('lognorm(X)')"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
